Search Results - (( using codification system algorithm ) OR ( variable mobile learning algorithm ))

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  1. 1

    IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE by ABDUL RAZAK, NUSRAH

    Published 2017
    “…Behaviour-based architecture is one of the most effective autonomous navigation techniques, second only to machine learning. However, specific algorithm may only be effective for a specific environment. …”
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    Final Year Project
  2. 2

    Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

    Published 2017
    “…Finally, the last objective is to improve the optimality of the new approach using a robust Machine Learning strategy. An adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order for the mobile robot to learn. …”
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    Thesis
  3. 3
  4. 4

    A highly interpretable fuzzy rule base using ordinal structure for obstacle avoidance of mobile robot by Samsudin, Khairulmizam, Ahmad, Faisul Arif, Mashohor, Syamsiah

    Published 2011
    “…In order to achieve high accuracy, a specially tailored Genetic Algorithm (GA) approach for reinforcement learning has been proposed to optimize the ordinal structure fuzzy controller. …”
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    Article
  5. 5
  6. 6

    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

    Published 2019
    “…This is further worsen by the use of single sensors modality and machine learning algorithms. Furthermore, developing robust and efficient methods are required to handle issues such as orientation and position displacement, sensor fusion and feature incompatibility, automatic feature representation, and how to minimize intra-class similarity and inter-class variability. …”
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    Thesis
  7. 7

    Detection of phishing websites using machine learning approaches by Farashazillah Yahya, Magnus Anai, Ryan Isaac W Mahibol, Sidney Allister Frankie, Rio Guntur Utomo, Chong Kim Ying, Eric Ling Nin Wei

    Published 2021
    “…The dataset consists of 11,055 observations and 32 variables. Three supervised learning models are implemented in this study: Decision Tree, K-Nearest Neighbour (KNN), and Random Forest. …”
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    Proceedings
  8. 8

    Discriminative feature representation for Malay children’s speech recognition / Seyedmostafa Mirhassani by Mirhassani, Seyedmostafa

    Published 2015
    “…In the next step, based on the cepstral features provided by the filterbanks a hierarchical phoneme classification is performed. Systems using the provided features were evaluated in phoneme recognition/classification task. …”
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    Thesis